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With the security situation in Cyberspace constantly becoming worse, Cyber threat detection has attracted a lot of researching attentions. In this paper, existing detection technologies are firstly reviewed. Secondly, a framework of capturing the abnormal traffic of botnets is proposed. Major modules and key detection techniques are presented at the same time. The hidden threat detection in physically...
Various network relationships in many complex social systems can be described effectively by multilayer networks, but we find that there are interactions between individuals attributes and their social relationships by a principle of homophily, which hence impact the process of information spread and social influence in complex social systems. In order to integrate individuals relationships and attributes...
DNA microarray experiments provide us with huge amount of gene expression data, which leads to a dimensional disaster for extracting features related to tumor. A wavelet package decomposition based feature extraction method for tumor classification was proposed, by which eigenvectors are extracted from gene expression profiles and used as the input of support vector machines classifier. Two well-known...
Botnet, a network of computers that are compromised and controlled by the attacker, is one of the most significant and serious threats to the Internet. Researchers have done plenty of research and made significant progress. As the extensive use and unique advantages of peer-to-peer (P2P) technology, the new advanced form of botnets with the P2P architecture have emerged and become more resilient to...
Blogs have become a typical online publication in Web2.0 era. The users of blogs interact with each other by publishing entries, reading and posting comments to other's entries, and discussing with friends. By these actions, information propagates from user to user on the social networks. This paper extracts the information flow hidden in entries and investigates the rules of information flow in both...
Gene expression data that is being used to gather information from tissue samples is expected to significantly improve the development of efficient tumor diagnosis and to provide understanding and insight into tumor related cellular processes. In this paper, we propose a novel feature selection approach which integrates the feature score criterion with factor analysis to further improve the SVM-based...
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